基于Kubernetes的调度算法综述

A review of scheduling algorithms based on Kubernetes

在云计算领域,资源管理和任务调度的优化对提升系统效率和资源利用率至关重要。Kubernetes(K8S)作为业界领先的容器编排工具,致力于应用程序容器的自动化部署、扩展和管理,其核心优势之一在于利用高效的调度算法实现容器的跨集群部署与执行,这一策略在提高应用系统可移植性、安全性、优化资源利用和集成部署方面发挥了重要作用,使其能够更加敏捷高效地应对不断变化的业务需求。鉴于此,有关于K8S的调度算法成为了业界研究的热点,全面调研和分析了K8S相关的调度算法及其在不同应用领域中的实际表现,特别关注三个领域:通用调度算法的改进、面向人工智能的调度策略以及基于弹性伸缩的调度技术。最后通过综合分析,揭示当前研究的不足之处和未来研究中亟待解决的问题,为进一步优化K8S的调度算法提供借鉴和参考。

In the field of cloud computing,optimization of resource management and task scheduling is crucial to improving system efficiency and resource utilization.As the industry's leading container orchestration tool,Kubernetes(K8S)is dedicated to the automated deployment,expansion and management of application containers.One of its core advantages is to use efficient scheduling algorithms to achieve cross-cluster deployment and execution of containers.This strategy plays an important role in application system portability,security,optimized resource utilization and integrated deployment,making it more agile and efficient in responding to changing business needs.In view of this,K8S scheduling algorithms have become a hot research topic in the industry.This article aims to comprehensively investigate and analyze K8S-related scheduling algorithms and their actual performance in different application fields,with special attention to three areas:improvement of general scheduling algorithms,artificial intelligence-oriented scheduling strategy and elastic scaling-based scheduling technology.Finally,through comprehensive analysis,the shortcomings of current research and issues that need to be solved in future research are revealed,providing reference for further optimizing the K8S scheduling algorithm.